We will cover how machine learning techniques might fit into
quantitative finance. This includes techniques to rank assets and
construct spread based portfolios, and which types of machine learning
applications don't work.

Scikit-learn is a popular Open Source library for Machine Learning in
Python. This presentation will introduce the project and give demo how
to use it in conjunction with other tools from the PyData ecosystem such
as NumPy, pandas and Jupyter notebook. Finally we will review recent
and ongoing developments if time allows.